Sep 30
A reminder to hand in your program in homework 1 electronically
by email to mdstone@cs.

Sep 11
Quick clarification on correlation, as used by Paskin to
describe the SLAM problem. Correlation can be
understood intuitively as the interdependence of variable
quantities. It is measured in terms of covariance.

...it is difficult to employ the covariance as an absolute measure
of dependence because its value depends on the scale of measurement
and so it is hard to determine whether a particular covariance is
large at first glance. This problem can be elimnated by
standardizing its value, using the simple coefficient of linear
correlation. The population linear coefficient of
correlation, ρ, is related to the covariance and is defined
as

ρ = covariance(X,Y)/(σ(X)σ(Y))

where σ(X) and σ(Y) are the standard deviations of X
and Y respectively. [Mendenhall et al, Math. Stats. with
Applications, PWS Kent 1990]